Method and device for encoding or decoding image

ABSTRACT

An image decoding method and apparatus according to an embodiment may extract, from a bitstream, a quantization coefficient generated through core transformation, secondary transformation, and quantization; generate an inverse-quantization coefficient by performing inverse quantization on the quantization coefficient; generate a secondary inverse-transformation coefficient by performing secondary inverse-transformation on a low frequency component of the inverse-quantization coefficient, the secondary inverse-transformation corresponding to the secondary transformation; and perform core inverse-transformation on the secondary inverse-transformation coefficient, the core inverse-transformation corresponding to the core transformation.

TECHNICAL FIELD

The present disclosure relates to image encoding and decoding methodsand apparatuses, and more particularly, to image encoding and decodingmethods and apparatuses which further efficiently perform prediction,motion compensation, transformation, and entropy coding.

BACKGROUND ART

Image data is encoded by a codec based on a predetermined datacompression standard, e.g., the Moving Picture Expert Group (MPEG)standard, and then is stored in the form of a bitstream in a recordingmedium or is transmitted via a communication channel.

As hardware for reproducing and storing high resolution or high qualityimage content is being developed and supplied, a need for a codec foreffectively encoding or decoding the high resolution or high qualityimage content is increasing. Encoded image content may be decoded to bereproduced. Recently, methods of efficiently compressing high resolutionor high quality image content are being performed. For example, anefficient image compressing method is performed by randomly processingan encoding-target image.

DETAILED DESCRIPTION OF THE INVENTION Technical Problem

Provided are an image encoding method or an image decoding method and animage encoding apparatus or an image decoding apparatus, which are aimedto increase an image compression rate.

Technical Solution

In accordance with an aspect of the present disclosure, an imagedecoding method includes extracting, from a bitstream, a quantizationcoefficient generated through core transformation, secondarytransformation, and quantization; generating an inverse-quantizationcoefficient by performing inverse quantization on the quantizationcoefficient; generating a secondary inverse-transformation coefficientby performing secondary inverse-transformation on a low frequencycomponent of the inverse-quantization coefficient, the secondaryinverse-transformation corresponding to the secondary transformation;and performing core inverse-transformation on the secondaryinverse-transformation coefficient, the core inverse-transformationcorresponding to the core transformation.

The image decoding method may further include obtaining, from thebitstream, information about whether to perform the secondaryinverse-transformation, and wherein the secondary inverse-transformationmay be performed based on the information about whether to perform thesecondary inverse-transformation.

The secondary inverse-transformation may be performed on a sub-groupunit in a transformation block, and a size of the sub-group unit may bedetermined based on a size of the transformation block or a quantizationparameter.

A type of the secondary inverse-transformation to be performed on thesub-group unit may be determined based on a location of the sub-groupunit.

In accordance with another aspect of the present disclosure, an entropydecoding method includes obtaining, from a received bitstream,probability information used in performing arithmetic decoding on acurrent bin by updating, by using a first probability model and a secondprobability model, previous probability information that was used inperforming arithmetic decoding on a previous bin; obtaining the currentbin by performing arithmetic decoding based on the obtained probabilityinformation; and obtaining a syntax element by de-binarizing theobtained current bin, wherein the first probability model and the secondprobability model each use a size of a window indicating a number ofbins decoded prior to the current bin, and a size of a window of thefirst probability model is less than a size of a window of the secondprobability model.

The size of the window of the first probability model and the size ofthe window of the second probability model may be obtained from thebitstream.

One of the size of the window of the first probability model and thesize of the window of the second probability model may have a fixedvalue.

In accordance with another aspect of the present disclosure, an imagedecoding method includes extracting, from a received bitstream,prediction mode information of a current block to be decoded; generatinga first prediction block with respect to the current block based on theextracted prediction mode information; extracting, from the bitstream,calculation information about a calculation in which each pixelconstituting the first prediction block and adjacent pixels of the eachpixel are used; generating a second prediction block by changing a pixelvalue of the each pixel via a calculation with respect to the each pixelconstituting the first prediction block and pixels positioned at upperand left portions of the each pixel, based on the extracted calculationinformation; extracting, from the bitstream, and reconstructing aresidual corresponding to a difference value between the current blockand the second prediction block; and decoding the current block byadding the residual and the second prediction block, wherein thecalculation information includes parameter index information, and theparameter index information includes a first weight parameter applied tothe each pixel constituting the first prediction block, a second weightparameter applied to a pixel positioned at the upper portion of the eachpixel, and a third weight parameter applied to a pixel positioned at theleft portion of the each pixel.

The parameter index information may be defined with respect to each ofcoding units respectively having 2N×2N and N×N sizes.

The parameter index information may be included in the prediction modeinformation.

The parameter index information may be obtained from the bitstream at alevel of a coding unit or a prediction unit.

In accordance with another aspect of the present disclosure, an imagedecoding method includes receiving a bitstream; determining whether toperform pixel unit motion compensation on a current block, based oninformation about whether the pixel unit motion compensation is limited,the information being extracted from the bitstream; when the pixel unitmotion compensation is performed, extracting, from the bitstream,information about a first motion vector and a second motion vectorrespectively indicating a first corresponding region and a secondcorresponding region which are most similar to the current block in afirst reference picture and a second reference picture; performing blockunit bi-directional motion compensation on the current block by usingthe first motion vector and the second motion vector; performing thepixel unit motion compensation on each pixel of the current block byusing pixels of the first reference picture and the second referencepicture; and generating a bi-directional motion prediction value of thecurrent block by using a result of the block unit bi-directional motioncompensation and a result of the pixel unit motion compensation.

The information about whether the pixel unit motion compensation islimited may include at least one of a coded block flag (CBF),information indicating whether to perform motion compensation by usingderived motion information, information indicating whether to performlocal illumination compensation, and information indicating whether toperform affine motion compensation, and when the CBF is not 0, themotion compensation is performed by using the derived motioninformation, the local illumination compensation is performed, or theaffine motion compensation is performed, the pixel unit motioncompensation may not be performed.

The performing of the pixel unit motion compensation may includegenerating a pixel unit motion compensation value of the each pixel ofthe current block by using horizontal and vertical direction gradientsof a first corresponding pixel of the first reference picturecorresponding to the each pixel of the current block, horizontal andvertical direction gradients of a second corresponding pixel of thesecond reference picture corresponding to the each pixel of the currentblock, and a horizontal direction displacement vector and a verticaldirection displacement vector determined by using the pixels of thefirst reference picture and the second reference picture.

The horizontal direction displacement vector and the vertical directiondisplacement vector may be determined to be horizontal and verticaldirection displacement vectors by which a difference value between afirst displacement value and a second displacement value becomes aminimum value, wherein the first displacement value is obtained bydisplacing the first corresponding pixel of the first reference picturein a window region having a predetermined size by using the horizontaland vertical direction displacement vectors and the horizontal andvertical direction gradients of the first corresponding pixel, and thesecond displacement value is obtained by displacing the secondcorresponding pixel of the second reference picture by using thehorizontal and vertical direction displacement vectors and thehorizontal and vertical direction gradients of the second correspondingpixel.

Advantageous Effects

An image encoding method and apparatus, and an image decoding method andapparatus corresponding to the image encoding method and apparatus mayprovide an effect by which prediction, motion compensation,transformation, and entropy coding are further efficiently performed.

DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram illustrating a configuration of an imageencoding apparatus, according to an embodiment.

FIG. 2 is a block diagram illustrating a configuration of an imagedecoding apparatus, according to an embodiment.

FIG. 3 is a block diagram illustrating configurations of image encodingand decoding apparatuses that perform core transformation and secondaryinverse-transformation, according to an embodiment.

FIG. 4 is a diagram of a sub-group that is a unit on which secondaryinverse-transformation is performed, according to an embodiment.

FIG. 5 is a diagram illustrating a range in which secondaryinverse-transformation is performed, according to an embodiment.

FIG. 6 is a flowchart of an image decoding method, according to anembodiment.

FIG. 7 is a block diagram illustrating a configuration of anentropy-encoder, according to an embodiment.

FIG. 8 is a diagram schematically illustrating an updating process of aprobability model.

FIG. 9 is a diagram for comparison between updated probabilities withrespect to a first probability model and a second probability model,according to an embodiment.

FIG. 10 is a block diagram illustrating a configuration of anentropy-decoder, according to an embodiment.

FIG. 11 is a flowchart of an entropy decoding method, according to anembodiment.

FIG. 12 is a block diagram illustrating a configuration of an imageencoding apparatus including a post-processor, according to anembodiment.

FIG. 13 illustrates an example of a 16×16 intra prediction mode.

FIG. 14 illustrates an example of a 4×4 intra prediction mode.

FIG. 15 is a reference diagram for describing an operation ofpost-processing a first prediction block, according to an embodiment.

FIG. 16 is another reference diagram illustrating an operation of thepost-processor, according to an embodiment.

FIG. 17 is a block diagram illustrating a configuration of an imagedecoding apparatus including a post-processor, according to anembodiment.

FIG. 18 is a flowchart illustrating an image encoding method, accordingto an embodiment.

FIG. 19 is a flowchart illustrating an image decoding method, accordingto an embodiment.

FIG. 20 is a block diagram illustrating a configuration of a motioncompensator, according to an embodiment.

FIG. 21 is a reference diagram for describing processes of block-basedbi-directional motion prediction and compensation, according to anembodiment.

FIG. 22 is a reference diagram for describing a process of performingpixel unit motion compensation, according to an embodiment.

FIG. 23 is a reference diagram for describing a process of determining ahorizontal direction displacement vector and a vertical directiondisplacement vector, according to an embodiment.

FIG. 24 is a reference diagram for describing a process of calculatinghorizontal and vertical direction gradients, according to an embodiment.

FIG. 25 is a reference diagram for describing a process of calculatinghorizontal and vertical direction gradients, according to anotherembodiment.

FIG. 26 is a table showing filter coefficients of a gradient calculatingfilter, according to another embodiment.

FIG. 27 is a flowchart of an image encoding method, according to anembodiment.

FIG. 28 is a flowchart of an image decoding method, according to anembodiment.

MODE OF THE INVENTION

Advantages and features of the present disclosure and methods ofaccomplishing the same may be understood more readily by reference tothe following detailed description of embodiments and the accompanyingdrawings. The present disclosure may, however, be embodied in manydifferent forms and should not be construed as being limited to theembodiments set forth herein. Rather, these embodiments are provided sothat this disclosure will be thorough and complete and will fully conveythe concept of the disclosure to one of ordinary skill in the art.

Hereinafter, terms that are used in the specification will be brieflydescribed, and the present disclosure will be described in detail.

All terms including descriptive or technical terms which are used hereinshould be construed as having meanings that are obvious to one ofordinary skill in the art. However, the terms may have differentmeanings according to an intention of one of ordinary skill in the art,precedent cases, or the appearance of new technologies. Also, some termsmay be arbitrarily selected by the applicant, and in this case, themeaning of the selected terms will be described in detail in thedetailed description of the invention. Thus, the terms used herein haveto be defined based on the meaning of the terms together with thedescription throughout the specification.

Throughout the specification, a singular form may include plural forms,unless there is a particular description contrary thereto.

Throughout the specification, when a part “includes” or “comprises” anelement, unless there is a particular description contrary thereto, thepart can further include other elements, not excluding the otherelements. Also, the term ‘unit’, as used herein, means, but is notlimited to, a software or hardware component, such as a FieldProgrammable Gate Array (FPGA) or Application Specific IntegratedCircuit (ASIC), which performs certain tasks. A unit may advantageouslybe configured to reside on the addressable storage medium and configuredto execute on one or more processors. Thus, a unit may include, by wayof example, components, such as software components, object-orientedsoftware components, class components and task components, processes,functions, attributes, procedures, subroutines, segments of programcode, drivers, firmware, microcode, circuitry, data, databases, datastructures, tables, arrays, and variables. The functionality providedfor in the components and units may be combined into fewer componentsand units or further separated into additional components and units.

Hereinafter, an ‘image’ may indicate a static image such as a stillimage of a video or may indicate a dynamic image such as a movingpicture that is the video itself.

The present disclosure will now be described more fully with referenceto the accompanying drawings for one of ordinary skill in the art to beable to perform the present disclosure without any difficulty. In thedrawings, for a more clear description of the present disclosure, partsor units that are not related to the descriptions are omitted.

Hereinafter, with reference to FIGS. 1 through 28, an image encodingapparatus, an image decoding apparatus, an image encoding method, and animage decoding method according to embodiments will now be described.

In more detail, with reference to FIGS. 1 and 2, rough configurations ofan image encoding apparatus and an image decoding apparatus according toembodiments will be described below. Also, with reference to FIGS. 3through 6, image encoding and decoding methods involving using coretransformation and secondary inverse-transformation will be describedbelow. Also, with reference to FIGS. 7 through 11, entropy encoding anddecoding methods involving using a first probability model and a secondprobability model will be described below. Also, with reference to FIGS.12 through 19, a method of post-processing a prediction block accordingto an embodiment will be described below. Also, with reference to FIGS.20 through 28, a method of performing motion compensation by a blockunit and a pixel unit will be described below.

Hereinafter, example embodiments of the present disclosure will now bedescribed with reference to the accompanying drawings.

FIG. 1 is a block diagram illustrating a configuration of an imageencoding apparatus, according to an embodiment.

An image encoding apparatus 100 according to an embodiment may include atransformer 125, a quantizer 130, an entropy-encoder 135, aninverse-quantizer 145, an inverse-transformer 150, a de-blocker 155, asample adaptive offset (SAO) performer 160, an intra-predictor 120, areconstructed picture buffer 110, and an inter-predictor 115.

The image encoding apparatus 100 according to an embodiment performsprocesses of encoding image data. That is, the intra-predictor 120performs intra prediction on coding units in an intra mode, from among acurrent image 105, per prediction unit, and the inter-predictor 115performs inter prediction on coding units in an inter mode by using thecurrent image 105 and a reference image obtained from the reconstructedpicture buffer 110 according to prediction units. The current image 105may be split into largest coding units and then the largest coding unitsmay be sequentially encoded. In this regard, the largest coding unitthat is to be split into coding units having a tree structure may beencoded.

Residual data is generated by removing prediction data regarding codingunits of each mode that is output from the intra-predictor 120 or theinter-predictor 115 from data regarding encoded coding units of thecurrent image 105, and the residual data is output as a quantizedtransformation coefficient according to transformation units via thetransformer 125 and the quantizer 130. The quantized transformationcoefficient is reconstructed as the residual data in a spatial domainthrough the inverse-quantizer 145 and the inverse-transformer 150. Thereconstructed residual data in the spatial domain is added to predictiondata for coding units of each mode that is output from theintra-predictor 120 or the inter-predictor 115 and thus is reconstructedas data in a spatial domain for coding units of the current image 105.The reconstructed data in the spatial domain is generated as areconstructed image through the de-blocker 155 and the SAO performer160. The generated reconstructed image is stored in the reconstructedpicture buffer 110. The reconstructed images stored in the reconstructedpicture buffer 110 may be used as reference images for inter predictionwith respect to another image. The transformation coefficient quantizedby the transformer 125 and the quantizer 130 may be output as abitstream 140 via the entropy-encoder 135.

The inter-predictor 115, the intra-predictor 120, the transformer 125,the quantizer 130, the entropy-encoder 135, the inverse-quantizer 145,the inverse-transformer 150, the de-blocker 155, and the SAO performer160 which are elements of the image encoding apparatus 100 according toan embodiment may perform an operation based on each coding unit fromamong coding units according to a tree structure according to eachlargest coding unit.

In particular, the intra-predictor 120 and the inter-predictor 115 maydetermine a partition mode and a prediction mode of each coding unitfrom among the coding units according to a tree structure by taking intoaccount a maximum size and a maximum depth of a current largest codingunit, and the transformer 125 may determine whether to split atransformation unit having a quadtree structure in each coding unit fromamong the coding units having a tree structure.

FIG. 2 is a block diagram illustrating a configuration of an imagedecoding apparatus, according to an embodiment.

An image decoding apparatus 200 according to an embodiment may includean entropy-decoder 215, an inverse-quantizer 220, an inverse-transformer225, a de-blocker 245, an SAO performer 250, an intra-predictor 240, areconstructed picture buffer 230, and an inter-predictor 235.

The entropy-decoder 215 obtains, from a bitstream 205, decoding-targetencoded image data and encoding information required for decoding. Theencoded image data is a quantized transformation coefficient, and theinverse-quantizer 220 and the inverse-transformer 225 reconstructresidual data from the quantized transformation coefficient.

The intra-predictor 240 performs intra prediction on a coding unit in anintra mode. The inter-predictor 235 performs inter prediction by using areference image with respect to the coding unit in an inter mode fromamong a current image, wherein the reference image is obtained from thereconstructed picture buffer 230.

Prediction data and residual data regarding coding units of each mode,which passed through the intra-predictor 240 or the inter-predictor 235,are summed, so that data in a spatial domain regarding coding units ofthe current image 205 may be reconstructed, and the reconstructed datain the spatial domain may be output as a reconstructed image 260 throughthe de-blocker 245 and the SAO performer 250. Also, reconstructed imagesthat are stored in the reconstructed picture buffer 230 may be output asreference images.

The entropy-decoder 215, the inverse-quantizer 220, theinverse-transformer 225, the intra-predictor 240, the inter-predictor235, the de-blocker 245, and the SAO performer 250 which are elements ofthe image decoding apparatus 200 according to an embodiment may performan operation based on each coding unit from among coding units accordingto a tree structure according to each largest coding unit.

In particular, the intra-predictor 240 and the inter-predictor 235 maydetermine a partition mode and a prediction mode of each coding unitfrom among the coding units according to a tree structure, and theinverse-transformer 225 may determine whether or not to split atransformation unit according to a quadtree structure in each codingunit.

Hereinafter, with reference to FIGS. 3 through 6, image encoding anddecoding methods involving using secondary transformation/inversetransformation will be described

FIG. 3 is a block diagram illustrating configurations of image encodingand decoding apparatuses that perform secondary transformation/inversetransformation, according to an embodiment.

Referring to FIG. 3, the image encoding apparatus includes a coretransformer 310, a secondary transformer 320, and a quantizer 330, andthe image decoding apparatus includes an inverse-quantizer 340, asecondary inverse-transformer 350, and a core inverse-transformer 360.The core transformer 310 and the secondary transformer 320 of FIG. 3 maybe included in the transformer 125 of FIG. 1, and the quantizer 330 maycorrespond to the quantizer 130 of FIG. 1. The inverse-quantizer 340 ofFIG. 3 corresponds to the inverse-quantizer 220 of FIG. 2, and thesecondary inverse-transformer 350 and the core inverse-transformer 360may be included in the inverse-transformer 225 of FIG. 2.

In order to efficiently compress an image, the image encoding apparatussplits each of frames into blocks, and the core transformer 310 performscore transformation on each of blocks of a frame. The core transformer310 may generate core transformation coefficients by performingtransformation on a residual block according to each of transformationunits. In this regard, a transformation unit may have a tree structurewithin a range of a maximum size and a minimum size, and whether acurrent block is split into sub-blocks may be indicated by a flagaccording to each of the transformation units. The core transformer 310may perform transformation based on discrete cosine transform (DCT)and/or discrete sine transform (DST). The core transformation accordingto an embodiment is applied to all coefficients in a block. In theprocessing process, energy in each block may be compressed into a smallnumber of large transformation coefficients and several smalltransformation coefficients.

The core transformation coefficients generated through the coretransformation by the core transformer 310 may be divided into alow-frequency component domain having a small number of largetransformation coefficients and a high-frequency component domain havingseveral small transformation coefficients. The secondary transformer 320according to an embodiment may perform secondary transformation on thelow-frequency component domain, thereby increasing quantizationperformance.

The secondary transformation according to an embodiment may be performedbased on DCT and/or DST as in the core transformation, and may be arandom type such as orthogonal transformation, rotationaltransformation, or the like. However, unlike the core transformationperformed on all of coefficients in a block, the secondarytransformation is performed on the low-frequency component domain. Thus,the secondary transformation is not performed on a coefficient of thehigh-frequency component domain, the coefficient being from among thecore transformation coefficients generated by the core transformer 310.

The secondary transformer 320 according to an embodiment may perform thesecondary transformation on a sub-group unit smaller than a size of atransformation unit. For example, the secondary transformer 320 mayperform the secondary transformation on transformation coefficients of alow-frequency component which are included in a 8×8-size sub group atthe top left which is a portion of a transformation unit.

The quantizer 330 according to an embodiment may quantize coefficientsthat have been transformed by the core transformer 310 and the secondarytransformer 320. The quantization coefficients are provided to theinverse-quantizer 340, and the inverse-quantizer 340 according to anembodiment performs inverse quantization on the quantizationcoefficients, thereby generating inverse-quantization coefficients. Theinverse-quantizer 340 according to an embodiment may performinverse-quantization on a Q_sub-groups unit smaller than a size of atransformation unit.

The secondary inverse-transformer 350 according to an embodimentgenerates a secondary inverse-transformation coefficient by performingsecondary inverse-transformation on a low frequency component of theinverse-quantization coefficient, wherein the secondaryinverse-transformation corresponds to the secondary transformation. Thecore inverse-transformer 360 according to an embodiment performs coreinverse-transformation on the secondary inverse-transformationcoefficient, wherein the core inverse-transformation corresponds to thecore transformation.

The secondary inverse-transformer 350 according to an embodiment mayperform the secondary inverse-transformation based on inverse DCT and/orinverse DST. Because the secondary inverse-transformation is performedon the low frequency component of the inverse-quantization coefficient,the secondary inverse-transformation is not performed on a highfrequency component of the inverse-quantization coefficient.

The secondary inverse-transformer 350 according to an embodiment mayperform the secondary inverse-transformation on a 2nd_tr_sub-group unitsmaller than a size of a transformation unit. For example, the secondaryinverse-transformer 350 may perform the secondary inverse-transformationon inverse-quantization coefficients of a low frequency component whichare included in a 8×8-size sub group at the top left which is a portionof a transformation unit.

The core inverse-transformer 360 according to an embodiment performsinverse transformation based on inverse DCT and/or inverse DST in a samemanner by the secondary inverse-transformer 350, but the coreinverse-transformer 360 performs the inverse transformation on allcoefficients in the transformation unit, unlike the secondaryinverse-transformation.

FIG. 4 is a diagram of a sub-group that is a unit on which secondaryinverse-transformation is performed, according to an embodiment.

Referring to FIG. 4, the secondary inverse-transformation may beperformed on sub-group units 412 and 422 positioned at the top left inrespective transformation units 410 and 420. Because the secondaryinverse-transformation is performed on the sub-group unit 412 or 422,high parallelism of a decoding operation may be maintained. However, inorder to maintain the parallelism, a condition may be applied to a sizeof a sub-group unit on which the secondary inverse-transformation isperformed. According to an embodiment, a condition indicating that thesub-group unit 412 on which the secondary inverse-transformation isperformed has to be smaller than a group unit (i.e.,coeff_coding_sub_group; 414) with which a quantization coefficient isobtained from a bitstream or a group unit (i.e., Q_sub-group; 414) onwhich inverse quantization is performed may be applied. However,according to an embodiment, a size of the sub-group unit 422 on whichthe secondary inverse-transformation is performed may be equal to thatof the group unit (i.e., coeff_coding_sub_group) with which aquantization coefficient is obtained from a bitstream or the group unit(i.e., Q_sub-group) on which inverse quantization is performed.

FIG. 5 is a diagram illustrating a range in which secondaryinverse-transformation is performed, according to an embodiment.

Referring to FIG. 5, the secondary inverse-transformation according toan embodiment may be performed on sub-group units 512 positioned at thetop left in a transformation unit 510. The sub-group units 512 mayindicate a domain corresponding to a low frequency component of aninverse-quantization coefficient. The secondary inverse-transformationaccording to an embodiment may be performed on sub-group units 522 and524 in a transformation unit 520, and types of the secondaryinverse-transformation may be determined depending on positions ofsub-groups, wherein the secondary inverse-transformation is performed onthe sub-groups based on the types, respectively. For example, inverseDCT may be performed on the sub-group units 522, and inverse DST may beperformed on the sub-group units 524. Sizes of sub-group units are notfixed. The sizes of the sub-group units may be different from each otherin a transformation unit, and may be determined based on positions ofthe sub-group units in the transformation unit. Information about thepositions, the sizes, or the like regarding the sub-group units to besecondary inverse-transformed may be signalled via bitstreams in therespective sub-group units.

According to an embodiment, when the image encoding apparatus 100applies secondary transformation to all transformation units, it is notnecessary to signal information indicating whether or not the secondarytransformation is performed to the image decoding apparatus 200.However, the image encoding apparatus 100 may compare costs ofbitstreams obtained by encoding transformation coefficients generated byapplying the secondary transformation, and may adaptively apply thesecondary transformation to make a minimum cost. Thus, when thesecondary transformation is applied to some transformation units, it isnecessary to signal the information indicating whether or not thesecondary transformation is performed to the image decoding apparatus200.

The information indicating whether or not the secondary transformationis performed may be included in other syntax elements. For example, theinformation indicating whether or not the secondary transformation isperformed may be included in information about a prediction mode, asplit depth, an intra prediction direction, a transformation skip mode,or the like. In addition, the information indicating whether or not thesecondary transformation is performed may be explicitly signalled by acoding unit, a transformation unit, a prediction unit or each sub-groupunit in the transformation unit. When all coefficients in thetransformation unit are 0 or coefficients have values equal to or lessthan a predetermined threshold value, the secondary transformation maynot be performed, and in this case, the signalling of the informationindicating whether or not the secondary transformation is performed maybe omitted.

The image decoding apparatus 200 according to an embodiment may obtain,from a bitstream, and use the information indicating whether or not thesecondary transformation is performed. The information indicatingwhether or not the secondary transformation is performed may be includedin the bitstream associated with various data units. For example, theimage decoding apparatus 200 may use parameter index informationincluded in a sequence parameter set, a picture parameter set, a videoparameter set, a slice header, and a slice segment header. Furthermore,the image decoding apparatus 200 may obtain and use syntax correspondingto the information indicating whether or not the secondarytransformation is performed, from a bitstream according to each largestcoding unit, each reference coding unit, each prediction unit, eachtransformation unit, or each sub-group unit in a transformation unit.

FIG. 6 is a flowchart of an image decoding method, according to anembodiment.

Referring to FIG. 6, in operation S610, the image decoding apparatus 200may extract, from a bitstream, a quantization coefficient obtained byquantizing a transformation coefficient generated through coretransformation and secondary transformation.

In operation S620, the image decoding apparatus 200 performs inversequantization on the quantization coefficient, thereby generating aninverse-quantization coefficient.

In operation S630, the image decoding apparatus 200 generates asecondary inverse-transformation coefficient by performing secondaryinverse-transformation on a low frequency component of theinverse-quantization coefficient, wherein the secondaryinverse-transformation corresponds to the secondary transformation.

In operation S640, the image decoding apparatus 200 performs coreinverse-transformation on the secondary inverse-transformationcoefficient, the core inverse-transformation corresponding to the coretransformation.

Hereinafter, with reference to FIGS. 7 through 11, entropy encoding anddecoding methods involving using a first probability model and a secondprobability model according to embodiments will now be described.

As illustrated above with reference to FIGS. 1 and 2, theentropy-encoder 135 of the image encoding apparatus 100 according to anembodiment entropy encodes a plurality of pieces of encodinginformation, e.g., syntax elements such as a quantized transformationcoefficient, a prediction mode of a prediction unit, a quantizationparameter, a motion vector, etc., which are generated with respect toeach coding unit. In more detail, the entropy-encoder 135 performscontext-based adaptive binary arithmetic coding (hereinafter, referredto as “CABAC”) on the syntax elements. Also, the entropy-decoder 215 ofthe image decoding apparatus 200 performs entropy decoding so as toobtain the syntax elements of a plurality of pieces of information to bedecoded.

FIG. 7 is a block diagram illustrating a configuration of anentropy-encoder, according to an embodiment. An entropy-encoder 700 ofFIG. 7 corresponds to the entropy-encoder 135 of FIG. 1.

Referring to FIG. 7, the entropy-encoder 700 according to an embodimentincludes a binarizer 710, a context modeller 720, and a binaryarithmetic coder 730. Also, the binary arithmetic coder 730 includes aregular coding engine 732 and a bypass coding engine 734.

Syntax elements input to the entropy-encoder 700 may not be binaryvalues, thus, when the syntax elements are not binary values, thebinarizer 710 binarizes the syntax elements and thus outputs a binstring consisting of binary values of 0 or 1. A bin indicates each bitof a stream consisting of 0 or 1, and is encoded based on CABAC. If asyntax element is data in which frequencies of 0 and 1 are equal, thesyntax element is output to the bypass coding engine 734 that does notuse a probability value and then is encoded.

The context modeller 720 provides a probability model with respect to acurrent encoding symbol to the regular coding engine 732. In moredetail, the context modeller 720 determines a probability of apredetermined binary value, based on previously-encoded symbols, andoutputs, to the binary arithmetic coder 730, an occurrence probabilityof a binary value for encoding a binary value of the current encodingsymbol. An existing context modeller provides a probability model for anencoding symbol by providing an occurrence probability of a mostprobable symbol (MPS) and a context index (i.e., ctxIdx) indicatinginformation which binary value from among 0 and 1 corresponds to theMPS. In contrast, the context modeller 720 according to an embodimentdoes not distinguish between an MPS and a least probable symbol (LPS),but determines P(1) indicating an occurrence probability of apredetermined binary value, e.g., “1”, based on a previously-encodedsymbol and provides the determined probability of the predeterminedbinary value to the binary arithmetic coder 730.

In addition, the context modeller 720 updates a probability of apredetermined binary value by using a plurality of probability models,based on a binary value of a current encoding symbol. A process ofupdating a probability of a predetermined binary value will be describedin detail below.

The regular coding engine 732 performs CABAC based on the probability ofthe predetermined binary value and the binary value of the currentencoding symbol which are provided from the context modeller 720. Thatis, the regular coding engine 732 may determine an occurrenceprobability P(1) of “1” and an occurrence probability P(0) of “0”, basedon the probability of the predetermined binary value provided from thecontext modeller 720, and may perform CABAC by changing a rangeindicating a probability range based on the binary value of the currentencoding symbol based on the determined occurrence probabilities P(0)and P(1).

FIG. 8 is a diagram schematically illustrating an updating process of aprobability model.

Referring to FIG. 8, when a probability state index pStateIdx in anexisting probability function is determined, if a value of an encodingsymbol is a value designated as an MPS, the probability state indexpStateIdx is updated such that a probability state transitions from acurrent probability state (i.e., state a) to a front-direction state(i.e., state σ+1) in which an LPS probability is decreased, and if thevalue of the encoding symbol is not the MPS, i.e., a value designated asan LPS, the probability state index pStateIdx is updated such that theprobability state transitions from the current probability state (i.e.,state a) to a rear-direction state (i.e., state σ−k(k>0)) in which aprobability of the LPS is increased. For example, when the currentprobability state index pStateIdx is C, if a value of a current encodingsymbol is a value designated as the LPS, the current encoding symbol isencoded and then the probability state index pStateIdx is updated to A.If a value of a next encoding symbol is a value designated as the MPS,the probability state index pStateIdx is re-updated from A to B.

As illustrated, a probability function may have an exponential shape. Inthe probability function having the exponential shape, a probabilitydistribution of an LPS being close to 0 is very thick, and a probabilitydistribution of an LPS being close to ½ is very thin. Thus, in a casebased on the probability function having the exponential shape, whenoccurrence probabilities of binary values of 0 and 1 are similar, i.e.,when the occurrence probabilities of the binary values of 0 and 1 areclose to ½, a distribution of a probability is thin, thus, a predictionerror with respect to the probability may increase. Also, when theprobability function having the exponential shape is used, a probabilityvalue that is close to 0 has to be finely expressed, thus, a bit depthexpressing the probability value may be increased. Thus, a size of alook-up table for storing a probability model having the probabilityfunction with the exponential shape may be increased. In addition,according to the related art, when a probability is updated or aprobability range is divided, if thick probability values are used, acomputation of multiplication is increased such that a load may beapplied to hardware.

Accordingly, the context modeller 720 according to an embodimentdetermines occurrence probabilities of binary values of 0 and 1, basedon a probability function having a uniform distribution. In addition,the context modeller 720 according to an embodiment may update aprobability of a predetermined binary value by using a plurality ofprobability models.

Hereinafter, a process of updating a probability model, the processbeing performed by the context modeller 720, will now be described indetail.

In CABAC, a probability update is performed by using Equation 1.

$\begin{matrix}{{P\_ new} = {\frac{y}{W} + {\left( {1 - \frac{1}{W}} \right){P\_ old}}}} & \left\lbrack {{Equation}\mspace{14mu} 1} \right\rbrack\end{matrix}$

In Equation 1, P_new indicates a probability of an updated LPS, P_oldindicates a probability of an LPS used in performing arithmetic codingon a current encoding symbol, and W (where W is an integer) indicatesthe number of previously-encoded symbols and is referred to as a windowsize. 1/W is a scaling factor, and when the current encoding symbol hasa binary value corresponding to a value of an MPS, y has a value of 0,and when the current encoding symbol has a binary value corresponding toa value of an LPS, y has a value of 1.

In an updating process with respect to a probability which is performedby using Equation 1, an important parameter is a scaling factor 1/W.Depending on a value of the scaling factor 1/W, sensitivity andstability of an entire CABAC encoding procedure which does not react tonoise or an error are determined. A process of determining anappropriate value of the scaling factor 1/W is difficult and consumingprocess.

Thus, in order to update a probability, the context modeller 720according to an embodiment generates a plurality of updatedprobabilities by using a first probability model and a secondprobability model having different scaling factors, and determines afinally-updated probability by using respective probabilities updatedusing the first probability model and the second probability model. Inother words, the first probability model and the second probabilitymodel may have different window sizes.

In more detail, the first probability model and the second probabilitymodel which are used by the context modeller 720 according to anembodiment are based on Equation 2 and Equation 3.

$\begin{matrix}{{P0\_ new} = {\frac{y}{W\; 0} + {\left( {1 - \frac{1}{W\; 0}} \right){P0\_ old}}}} & \left\lbrack {{Equation}\mspace{14mu} 2} \right\rbrack \\{{P1\_ new} = {\frac{y}{W\; 1} + {\left( {1 - \frac{1}{W\; 1}} \right){P1\_ old}}}} & \left\lbrack {{Equation}\mspace{14mu} 3} \right\rbrack\end{matrix}$

In Equation 2, P0_new indicates a probability of a predetermined binaryvalue updated based on the first probability model using a window sizeW0, and P0_old indicates a probability of a predetermined binary valueused in performing arithmetic coding on a current encoding symbol. InEquation 3, P1_new indicates a probability of a predetermined binaryvalue updated based on the second probability model using a window sizeW1, and P1_old indicates a probability of the predetermined binary valueused in performing arithmetic coding on the current encoding symbol.According to an embodiment, a size of W0 of the first probability modeland a size of W1 of the second probability model may be different fromeach other. For example, W0 may be less than W1. In Equation 2 andEquation 3, P0_new, P0_old, P1_new, or P1_old indicates an occurrenceprobability of the predetermined binary value that is 0 or 1. That is, aprobability used in an embodiment indicates an occurrence probability ofa particular binary value, e.g., “1”, neither an MPS nor an LPS. Indescriptions below, it is assumed that the predetermined binary value is1, that is, P_new or P_old indicates an occurrence probability of “1”.However, it is not limited thereto, thus, even when it is set that P_newor P_old indicates an occurrence probability of “0”, the updatingprocess with respect to a probability according to the embodiment may besimilarly applied thereto.

When probabilities P0_new and P1_new are obtained based on Equation 2,the context modeller 720 calculates a finally-updated probability P_newby using Equation 4 below.P _(new)=(P0_(new) +P1_(new)+1)>>1  [Equation 4]

In a CABAC encoding procedure, an entropy reset is performed accordingto each slice unit. The entropy reset means that CABAC is performed in amanner that a current probability value is discarded, and then CABACencoding is newly performed based on a predetermined probability value.A probability value set as an initial value in a probability updatingprocess performed after the reset process is not an optimal value, andafter an updating process is performed several times, probability valuesare converged on a predetermined probability value.

FIG. 9 is a diagram for comparison between updated probabilities withrespect to a first probability model and a second probability model,according to an embodiment.

In a graph of FIG. 9, it is set that a window size W0 of a firstprobability model 910 is less than a window size W1 of a secondprobability model 920. For example, a window size of the firstprobability model 910 may be 16, and a window size of the secondprobability model 920 may be 256.

Referring to FIG. 9, when the first probability model 910 having arelatively small window size is used, the more the probability update isperformed, the faster the probability is changed to be quickly convergedon a certain range, but when the update is repeated, fluctuation easilyoccurs. On the other hand, when the second probability model 920 havinga relatively large window size is used, a probability is not quicklychanged but once updated probabilities are converged on a predeterminedrange, fluctuation rarely occurs, thus, sensitivity to an error or noiseis very small and an operation is stable.

Thus, the context modeller 720 may adaptively adjust sizes of W0 and W1by taking into account the probability updating processes of the firstprobability model and the second probability model. For example, thecontext modeller 720 may perform a probability updating process in amanner that the context modeller 720 sets a size of W1 as a large size(e.g., W1=∞) during a threshold number of times after the entropy resetis performed, and after the threshold number of times, the contextmodeller 720 may adjust the size of W1 for stability of a system.

FIG. 10 is a block diagram illustrating a configuration of anentropy-decoder, according to an embodiment.

An entropy-decoder 1000 of FIG. 10 may correspond to the aforementionedentropy-decoder 215 of FIG. 2.

Referring to FIG. 10, the entropy-decoder 1000 includes a contextmodeller 1010, a regular decoder 1020, a bypass decoder 1030, and ade-binarizer 1040. The entropy-decoder 1000 performs an inverse processof an entropy encoding process performed by the entropy-encoder 700.

A symbol encoded due to bypass coding is output to and thus is decodedby the bypass decoder 1030, and a symbol encoded due to regular codingis decoded by the regular decoder 1020. The regular decoder 1020performs arithmetic decoding on a binary value of a current encodingsymbol by using a probability of a predetermined binary value determinedbased on previously-encoded symbols that were decoded prior to thecurrent encoding symbol provided by the context modeller 1010. Asdescribed above, because a binary value indicating a representativevalue of a predetermined probability range is transmitted as an encodedsymbol according to a binary arithmetic coding result, the regulardecoder 1020 may decode encoded symbols by using occurrenceprobabilities of 0 and 1.

The context modeller 1010 updates the probability of the predeterminedbinary value by using a plurality of scaling factors, based on thebinary value of the decoded encoding symbol. As described above, thecontext modeller 1010 does not distinguish between an MPS and an LPS,but determines P(1) indicating an occurrence probability of thepredetermined binary value, e.g., “1”, based on the previously-encodedsymbols and provides the determined probability of the predeterminedbinary value to the regular decoder 1020. The de-binarizer 1040reconstructs bin strings to syntax elements, the bin strings having beenreconstructed by the regular decoder 1020 or the bypass decoder 1030.

As described above, the first probability model and the secondprobability model may be adaptively selected based on content. Forexample, the first probability model and the second probability modelmay be determined based on a slice or a picture. Also, the window sizeW0 of the first probability model and the window size W1 of the secondprobability model may be adaptively determined and may be signalled fromthe image encoding apparatus 100 to the image decoding apparatus 200 viaa bitstream. In this regard, values of W0 and W1 may be signalled in aunit of group of pictures (GOP), a slice, a largest coding unit, or thelike.

According to an embodiment, a value of one of W0 and W1 may be set as afixed value, and only the other value may be signalled via a bitstream.In this regard, the fixed value of a window size may depend on a type ofa picture or a slice.

According to an embodiment, W0 and W1 may all have fixed values, and inthis case, a separate syntax element to indicate the values of W0 and W1is not required to be signalled. On the other hand, when values of W0and W1 vary, the values of W0 and W1 may be obtained from a bitstream ormay be determined based on a slice type or a picture type.

FIG. 11 is a flowchart of an entropy decoding method, according to anembodiment.

Referring to FIG. 11, in operation S1110, the entropy-decoder 1000 mayobtain, from a received bitstream, probability information used inperforming arithmetic decoding on a current bin by updating, by using afirst probability prediction model and a second probability predictionmodel, previous probability information that was used in performingarithmetic decoding on a previous bin.

In operation S1120, the entropy-decoder 1000 obtains a bin by performingarithmetic decoding based on the obtained probability information.

In operation S1130, the entropy-decoder 1000 obtains a syntax element byde-binarizing the obtained bin.

Hereinafter, with reference to FIGS. 12 through 19, a method ofpost-processing a prediction block according to an embodiment will nowbe described.

FIG. 12 is a block diagram illustrating a configuration of an imageencoding apparatus including a post-processor, according to anembodiment.

Referring to FIG. 12, an image encoding apparatus 1200 includes apredictor 1210, a transformer and quantizer 1220, an entropy coding unit1230, and a post-processor 1240.

The predictor 1210 performs inter prediction and intra prediction. Theinter prediction refers to prediction with respect to a current block byusing a reference picture that is previously encoded, reconstructed andstored. The inter prediction is performed by a motion estimator 1211 anda motion compensator 1212. The intra prediction refers to predictionwith respect to a current block by using a pixel of a block that isadjacent to a block to be predicted. The intra prediction is performedby an intra predictor 1213.

FIG. 13 illustrates an example of a 16×16 intra prediction mode, andFIG. 14 illustrates an example of a 4×4 intra prediction mode.

Referring to FIG. 13, the 16×16 intra prediction mode includes fourmodes which are a vertical mode, a horizontal mode, a direct current(DC) mode, and a plane mode. In addition, referring to FIG. 14, the 4×4intra prediction mode includes nine modes which are a vertical mode, ahorizontal mode, a DC mode, a diagonal down-left mode, a diagonaldown-right mode, a vertical right mode, a vertical left mode, ahorizontal-up mode, and a horizontal-down mode.

For example, an operation of prediction encoding a current block havinga size of 4×4 according to a mode 0 of FIG. 14, i.e., according to thevertical mode of FIG. 3 will be described. First, pixel values of pixelsA to D that are adjacent to an upper portion of the current block havingthe size of 4×4 are predicted as pixel values of the 4×4 current block.In other words, the value of the pixel A is predicted as four pixelvalues included in a first column of the 4×4 current block, the value ofthe pixel B is predicted as four pixel values included in a secondcolumn of the 4×4 current block, the value of the pixel C is predictedas four pixel values included in a third column of the 4×4 currentblock, and the value of the pixel D is predicted as four pixel valuesincluded in a fourth column of the 4×4 current block. In this manner,the prediction block that is generated by the intra prediction by whicha value of an adjacent pixel is extended in a predetermined directionhas predetermined directivity according to a prediction mode. Predictionefficiency may be improved when pixels of a current block to be encodedhave predetermined directivity, however, when pixels of the currentblock do not have directivity, prediction efficiency may deteriorate.Thus, as will be described below, the post-processor 1240 of the imageencoding apparatus according to the present disclosure changes a pixelvalue of each pixel inside the prediction block by performing anoperation using each pixel inside the prediction block and at least oneadjacent pixel, which is a post-processing operation with respect to theprediction block generated through the intra prediction, and generates anew prediction block, thereby improving image prediction efficiency.

Referring back to FIG. 12, the transformer and quantizer 1220 transformsand quantizes residual, which is a difference value between a predictionblock and an original image block respectively output from the predictor1210 and the post-processor 1240, and the entropy coding unit 1230performs compression by performing variable length encoding on thequantized residual information. The encoded residual is reconstructed byan inverse-quantizer 1214 and an inverse-transformer 1215, and an adder1216 adds the reconstructed residual to the prediction block so as toreconstruct the current block. The reconstructed block is stored in astorage unit (not shown) and is used as reference data when a next blockis encoded.

Hereinafter, an operation of post-processing a prediction block, theoperation being performed by the post-processor 1240 of FIG. 12, willnow be described.

The post-processor 1240 changes a pixel value of each of pixelsconstituting a first prediction block by performing a calculation usingeach pixel of a first prediction block generated by the intra predictor1213 and at least one adjacent pixel, thereby generating a secondprediction block. In this regard, the intra predictor 1213 generates thefirst prediction block by using a general intra prediction method.

FIG. 15 is a reference diagram for describing an operation ofpost-processing a first prediction block, according to an embodiment. InFIG. 15, reference numerals 1510 through 1560 represent a process ofchanging each pixel value inside the first prediction block processed bythe post-processor 1240 in a time sequence.

Referring to FIG. 15, the post-processor 1240 according to an embodimentchanges a pixel value of each pixel of the first prediction block bycalculating an average value by applying a weight to each of pixelvalues of a pixel to be changed inside a first prediction block 1510 andadjacent pixels positioned at upper and left portions of the pixel. Forexample, in FIG. 15, when a pixel value of a pixel 1521 to be changed ofthe first prediction block 1510 is P[1][1], a pixel value of a pixel1522 positioned at an upper portion is P[0][1], a pixel value of a pixel1523 positioned at a left portion is P[1][0], and a value obtained bychanging the pixel value P[1][1] of the pixel 1521 is P′[1][1], P′[1][1]may be calculated by using Equation 5 below.

$\begin{matrix}{{{P^{\prime}\lbrack 1\rbrack}\lbrack 1\rbrack} = \frac{{\alpha\;{{P\lbrack 1\rbrack}\lbrack 1\rbrack}} + {\beta\;{{P\lbrack 0\rbrack}\lbrack 1\rbrack}} + {\gamma\;{{P\lbrack 1\rbrack}\lbrack 0\rbrack}} + 2}{4}} & \left\lbrack {{Equation}\mspace{14mu} 5} \right\rbrack\end{matrix}$

In Equation 5, α indicates a first weight parameter applied to P[1][1],β indicates a second weight parameter applied to P[0][1] that is a pixelvalue of a pixel positioned at an upper portion of P[1][1, and γindicates a third weight parameter applied to P[1][0] that is a pixelvalue of a pixel positioned at a left portion of P[1][1].

As illustrated in FIG. 15, the post-processor 1240 according to anembodiment changes a pixel value of each pixel of the first predictionblock by applying a weight to a pixel value of a pixel to be changed andeach of pixel values of adjacent pixels positioned at upper and leftportions of the pixel from the uppermost and left portions to thelowermost and right portions of each pixel inside the first predictionblock. However, the operation of post-processing the first predictionblock is not limited to the above described manner i.e. from theuppermost and left portions to the lowermost and right portions, andthus may be sequentially performed on each of pixels of the firstprediction block from the uppermost and right portions to the lowermostand left portions, from the lowermost and right portions to theuppermost and left portions, or from the lowermost and left portions tothe uppermost and right portions. For example, in an opposite order tothe order of processing illustrated in FIG. 15, when pixels of the firstprediction block are changed from the lowermost and right portions tothe uppermost and left portions, a pixel value of each pixel of thefirst prediction block is changed via a calculation using a pixel to bechanged and pixels positioned at lower and right portions of the pixel.

FIG. 16 is another reference diagram illustrating an operation of thepost-processor 1240, according to an embodiment. In FIG. 16, referencenumeral 1610 indicates a first pixel of a first prediction block to becurrently changed, and reference numeral 1611 indicates a second pixelpositioned at an upper portion of a first pixel 1610, and referencenumeral 1612 indicates a third pixel positioned at a left portion of thefirst pixel 1610.

The operation of the post-processor 1240 according to an embodiment isgeneralized below with reference to FIG. 16. When the size of the firstprediction block is m×n (where m and n are positive integers), a pixelvalue of the first pixel 1610 which is to be changed and is positionedin an i-th (where i is an integer from 0 to m−1) column and a j-th(where j is an integer from 0 to n−1) row inside the first predictionblock is P[i][j], a pixel value of the second pixel 1612 positioned at aleft portion of the first pixel 1610 is P[i][j−1], and a pixel value ofthe third pixel 1611 positioned at an upper portion of the first pixel1610 is P[i−1][j], the pixel value of the first pixel 1610 is changedinto P′[i][j] by using Equation 6.P′[i][j]=(αP[i][j]+βP[i−1][j]+γP[i][j−1]+2)>>2  [Equation 6]

In Equation 6, α indicates a first weight parameter applied to P[i][j],β indicates a second weight parameter applied to P[i−1][j] that is apixel value of a pixel positioned at an upper portion of P[i][j], and γindicates a third weight parameter applied to P[i][j−1] that is a pixelvalue of a pixel positioned at a left portion of P[i][j]. According toan embodiment, when a position of a pixel to be changed becomes distantfrom a boundary of the first prediction block, a value of a weightparameter β or γ may be decreased. Relations among weight parameters α,β and γ may be determined base on a relation of Equation 7 below.α+β+γ=2^(P)  [Equation 7]

In Equation 7, P indicates an integer equal to or greater than 0.

The post-processor 1240 generates a second prediction block by changinga pixel value by applying Equation 2 to all pixels inside the firstprediction block 1600 from the uppermost and left portions to thelowermost and right portions.

The image encoding apparatus 1200 according to an embodiment may comparecosts of bitstreams obtained by encoding second prediction blocksgenerated by applying various weights, and may add weight information(i.e., the first through third weight parameters) which is used ingenerating a second prediction block having a lowest cost to a headerregion of the bitstreams. In this regard, information about the firstthrough third weight parameters is described as parameter indexinformation as in Table 1.

TABLE 1 Parameter 2N × 2N intra coding unit N × N intra coding unitIndex α β γ α β γ 0 8 0 0 8 0 0 1 4 2 2 6 1 1 2 4 4 0 6 2 0 3 4 0 4 6 02

In Table 1 above, parameter index information may be defined withrespect to each of coding units respectively having 2N×2N and N×N sizes.The parameter index information according to an embodiment may besignalled from an image encoding apparatus to an image decodingapparatus in various manners. For example, the parameter indexinformation may be included in information about a prediction mode.Also, the parameter index information may be included in informationindicating a block size, information indicating a partition shape of ablock, information indicating a luminance or chrominance component, orthe like, and may be signalled. According to an embodiment, theparameter index information may be explicitly signalled at a level of acoding unit or a prediction unit.

When the image encoding apparatus 1200 according to an embodimentdivides a coding unit into smaller blocks and performs prediction, theimage encoding apparatus 1200 may generate a second prediction block byapplying different weights to respective blocks, and in order tosimplify a calculation and decrease an overhead rate, the image encodingapparatus 1200 may allow same weight information to be applied to blocksincluded in a same coding unit.

FIG. 17 is a block diagram illustrating a configuration of an imagedecoding apparatus including a post-processor, according to anembodiment.

Referring to FIG. 17, an image decoding apparatus 1700 includes anentropy-decoder 1710, a re-aligner 1720, an inverse-quantizer 1730, aninverse-transformer 1740, an adder 1745, a motion compensator 1750, anintra predictor 1760, a filter 1770, and a post-processor 1780.

The entropy-decoder 1710 receives a compressed bitstream, and performsentropy decoding, thereby extracting post-processing calculation modeinformation used in generating prediction mode information of a currentblock and a second prediction block.

The image decoding apparatus 1700 according to an embodiment may obtain,from a bitstream, and use weight parameter information used ingenerating the second prediction block. The weight parameter information(or parameter index information) may be included in the bitstreamrelated with various data units. For example, the image decodingapparatus 1700 may use the parameter index information included in asequence parameter set, a picture parameter set, a video parameter set,a slice header, and a slice segment header.

Furthermore, the image decoding apparatus 1700 may obtain, from thebitstream, and use syntax corresponding to the parameter indexinformation according to each largest coding unit, each reference codingunit, and each prediction unit.

The entropy-decoder 1710 according to an embodiment performs entropydecoding on texture data, thereby extracting a quantized transformationcoefficient of a current block. The inverse-quantizer 1730 and theinverse-transformer 1740 performs inverse quantization and inversetransformation on the quantized transformation coefficient, therebyreconstructing residual corresponding to a difference between thecurrent block and the second prediction block. The motion compensator1750 and the intra predictor 1760 outputs a prediction block bygenerating the prediction block based on the prediction mode of thecurrent block. When the current block is encoded by using the secondprediction block generated by the post-processor 1240 of FIG. 12, thepost-processor 1780 generates the second prediction block by changingeach pixel value of the first prediction block generated by the intrapredictor 1760 based on post-processing calculation informationextracted from the bitstream. An operation of the post-processor 1780 ofthe image decoding apparatus 1700 is equal to an operation of thepost-processor 1240 of FIG. 12 in that the second prediction block isgenerated based on the post-processing calculation information extractedfrom the bitstream.

The adder 1745 adds the reconstructed residual to prediction blocksgenerated by the motion compensator 1750 and the intra predictor 1760,thereby reconstructing the current block. In particular, when thecurrent block to be decoded was encoded based on the second predictionblock according to the embodiments, the adder 1745 adds thereconstructed residual to the second prediction block generated by thepost-processor 1780, thereby reconstructing the current block. Thedecoded block is stored in a predetermined memory via the filter 1770and then is used as reference data in decoding a next block.

FIG. 18 is a flowchart illustrating an image encoding method, accordingto an embodiment.

Referring to FIG. 18, in operation S1810, a first prediction block withrespect to a current block to be encoded is generated. In this regard,the first prediction block is an intra prediction block that isgenerated by using a general intra prediction method.

In operation S1820, a second prediction block is generated by changing apixel value of each pixel of the first prediction block via acalculation using each pixel constituting the first prediction block andpixels positioned at upper and left portions of each pixel. As describedabove in the embodiment of the post-processor 1240, the secondprediction block is generated by changing the pixel value of each pixelof the first prediction block by using a calculation in which a weightis applied to upper and left pixels with respect to a pixel to bechanged in the first prediction block.

In operation S1830, residual that is a difference value between thecurrent block and the second prediction block is transformed, quantized,and entropy encoded, such that a bitstream is generated. Calculationinformation used in generating the second prediction block is added to apredetermined region of the generated bitstream, thus, a decodingapparatus may generate the second prediction block with respect to thecurrent block.

FIG. 19 is a flowchart illustrating an image decoding method, accordingto an embodiment.

Referring to FIG. 19, in operation S1910, prediction mode information ofa current block to be decoded is extracted from a received bitstream.

In operation S1920, a first prediction block with respect to the currentblock is generated based on the extracted prediction mode information.

In operation S1930, calculation information about a calculation in whicheach pixel constituting the first prediction block and adjacent pixelsof each pixel are used is extracted from the bitstream.

In operation S1940, a second prediction block is generated by changing apixel value of each pixel via a calculation with respect to each pixelconstituting the first prediction block and pixels positioned at upperand left portions of each pixel, based on the extracted calculationinformation.

In operation S1950, residual corresponding to a difference value betweenthe current block and the second prediction block is extracted from thebitstream and then is reconstructed.

In operation S1960, the residual and the second prediction block areadded such that the current block is decoded.

Hereinafter, with reference to FIGS. 20 through 28, a method ofperforming motion compensation by a block unit and a pixel unitaccording to an embodiment will now be described.

FIG. 20 is a block diagram illustrating a configuration of a motioncompensator, according to an embodiment. A motion compensator 2000 ofFIG. 20 may be included in the inter-predictor 115 of FIG. 1. Also, themotion compensator 2000 of FIG. 20 may be included in theinter-predictor 235 of FIG. 2.

Referring to FIG. 20, the motion compensator 2000 according to anembodiment includes a block unit motion compensator 2010, a pixel unitmotion compensator 2020, and a prediction value generator 2030.

The block unit motion compensator 2010 performs block unitbi-directional motion compensation on a current block to be encoded, byusing bi-directional motion vectors determined by a motion estimator(not shown) included in the inter-predictor 115 of FIG. 1 or theinter-predictor 235 of FIG. 2.

The pixel unit motion compensator 2020 additionally performs pixel unitmotion compensation on each pixel of the current block that isbi-directionally motion compensated in a block unit, by using pixels ofreference pictures indicated by the bi-directional motion vectors.

The prediction value generator 2030 generates a final bi-directionalmotion prediction value of the current block by using results of theblock unit bi-directional motion compensation and pixel unit motioncompensation. Hereinafter, processes of block unit bi-directional motionprediction and compensation and pixel unit bi-directional motioncompensation according to embodiments will be described in detail.

FIG. 21 is a reference diagram for describing processes of block-basedbi-directional motion prediction and compensation, according to anembodiment.

Referring to FIG. 21, the motion estimator (not shown) included in theinter-predictors 115 and 235 performs bi-directional motion predictionto search for a region most similar to a current block 2101 to beencoded in a current picture 2100 from a first reference picture 2110and a second reference picture 2120. In this regard, it is assumed thatthe first reference picture 2110 is a previous picture of the currentpicture 2100 and the second reference picture 2120 is a followingpicture of the current picture 2100. As a result of performing thebi-directional motion prediction, a first corresponding region 2112 mostsimilar to the current block 2101 in the first reference picture 2110and a second corresponding region 2122 most similar to the current block2101 in the second reference picture 2120 are determined. Also, a firstmotion vector MV1 based on a location difference between a block 2111 atthe same location as the current block 2101 in the first referencepicture 2110 and the first corresponding region 2112, and a secondmotion vector MV2 based on a location difference between a block 2121 atthe same location as the current block 2101 in the second referencepicture 2120 and the second corresponding region 2122 are determined.

The block unit motion compensator 2010 according to an embodimentperforms block unit bi-directional motion compensation on the currentblock 2101 by using the first and second motion vectors MV1 and MV2. Forexample, when P0(i,j) indicates a pixel value of the first referencepicture 2110 located at (i,j) (where i and j are each an integer),P1(i,j) indicates a pixel value of the second reference picture 2120located at (i,j), MV1=(MVx1,MVy1), and MV2=(MVx2, MVy2), a block unitbi-directional motion compensation value P_BiPredBlock(i,j) of a pixellocated at (i,j) of the current block 2101 may be calculated accordingto equation, P_BiPredBlock(i,j)={P0(i+MVx1, j+MVy1)+P1(i+MVx2,j+MVy2)}/2. In this manner, the block unit motion compensator 2010performs block unit motion compensation on the current block 2101 byusing an average value or a weighted sum of pixels of the first andsecond corresponding regions 2112 and 2122 respectively indicated by thefirst and second motion vectors MV1 and MV2.

The pixel unit motion compensator 2020 according to an embodimentperforms pixel unit motion compensation on the current block 2101 basedon an optical flow of pixels of the first and second reference pictures2110 and 2120.

An optical flow means a pattern of apparent motion of an object orsurface generated due to a relative movement between an observer (eyesor a camera) and a scene. In a video sequence, the optical flow may beexpressed by calculating motion between frames obtained at predeterminedtimes t and t+Δt. I(x,y,t) denotes a pixel value located at (x,y) in theframe at the predetermined time t. That is, I(x,y,t) is a value that isspatio-temporally changed. Equation 8 below is obtained bydifferentiating I(x,y,t) according to time t.

$\begin{matrix}{\frac{dI}{dt} = {{\frac{\partial I}{\partial x}\frac{dx}{dt}} + {\frac{\partial I}{\partial y}\frac{dy}{dt}} + \frac{\partial I}{\partial t}}} & \left\lbrack {{Equation}\mspace{14mu} 8} \right\rbrack\end{matrix}$

When it is assumed that a pixel value is changed according to motionwith respect to a small moving region in a block but is not changedaccording to time, dI/dt is 0. Also, when Vx denotes a displacementvector in an x-axis direction of the pixel value I(x,y,t) and Vy denotesa displacement vector in a y-axis direction of the pixel value I(x,y,t)in dx/dt, Equation 1 may be represented according to Equation 9 below

$\begin{matrix}{{\frac{\partial I}{\partial t} + {{Vx} \cdot \frac{\partial I}{\partial x}} + {{Vy} \cdot \frac{\partial I}{\partial y}}} = 0} & \left\lbrack {{Equation}\mspace{14mu} 9} \right\rbrack\end{matrix}$

In this regard, sizes of the displacement vector Vx in the x-axisdirection and displacement vector Vy in the y-axis direction may have avalue smaller than pixel accuracy used in bi-directional motionprediction. For example, when pixel accuracy is ¼ during bi-directionalmotion prediction, the sizes of displacement vectors Vx and Vy may havea value smaller than ¼.

The pixel unit motion compensator 2020 according to an embodimentcalculates the displacement vectors Vx and Vy by using Equation 5, andperforms pixel unit motion compensation by using the displacementvectors Vx and Vy. Since the pixel value I(x,y,t) is a value of anoriginal signal in Equation 9, massive overhead may be caused duringencoding when the value of the original signal is used as it is.Accordingly, the pixel unit motion compensator 2020 calculates thedisplacement vectors Vx and Vy by using Equation 5 by using the pixelsof the first and second reference pictures determined based on the blockunit bi-directional motion prediction.

FIG. 22 is a reference diagram for describing a process of performingpixel unit motion compensation, according to an embodiment.

In FIG. 22, it is assumed that a first corresponding region 2210 and asecond corresponding region 2220 respectively correspond to the firstcorresponding region 2112 and the second corresponding region 2122 ofFIG. 21, and are shifted by using the first and second motion vectorsMV1 and MV2 so as to overlap a current block 2200. Also, P(i,j)indicates a pixel located at (i,j) (where i and j are each an integer)bi-directionally predicted in the current block 2200, P0(i,j) indicatesa pixel value of a first corresponding pixel of a first referencepicture corresponding to the pixel P(i,j), and P1(i,j) indicates a pixelvalue of a second corresponding pixel of a second reference picturecorresponding to the pixel P(i,j). In other words, the pixel valueP0(i,j) of the first corresponding pixel corresponds to a pixel value ofthe pixel P(i,j) of the current block 2200 determined by the firstmotion vector MV1 indicating the first reference picture, and the pixelvalue P1(i,j) of the second corresponding pixel corresponds to a pixelvalue of the pixel P(i,j) of the current block 2200 determined by thesecond motion vector MV2 indicating the second reference picture.

Also, GradX0(i,j) indicates a horizontal direction gradient of the firstcorresponding pixel, GradY0(i,j) indicates a vertical direction gradientof the first corresponding pixel, GradX1(i,j) indicates a horizontaldirection gradient of the second corresponding pixel, and GradY1(i,j)indicates a vertical direction gradient of the second correspondingpixel. Also, d0 indicates a temporal distance between a current pictureof the current block 2200 and the first reference picture of the firstcorresponding region 2210 and d1 denotes a temporal distance between thecurrent picture and the second reference picture of the secondcorresponding region 2220.

When d0 and d1 are assumed as 1,

$\frac{\partial I}{\partial t}$in Equation 9 may approximate to the amount of change in the pixel valueP0(i,j) of the first corresponding pixel and the pixel value P1(i,j) ofthe second corresponding pixel according to time, as shown in Equation10 below.

$\begin{matrix}{\frac{\partial I}{\partial t} \approx {\left( {{p\; 0\left( {i,j} \right)} - {p\; 1\left( {i,j} \right)}} \right)/2}} & \left\lbrack {{Equation}\mspace{14mu} 10} \right\rbrack\end{matrix}$

The gradients

$\frac{\partial I}{\partial x}\mspace{14mu}{and}\mspace{14mu}\frac{\partial I}{\partial y}$in Equation 10 may respectively approximate to an average value ofhorizontal direction gradients of the first and second correspondingpixels and an average value of vertical direction gradients of the firstand second corresponding pixels according to Equations 11 and 12 below.

$\begin{matrix}{\frac{\partial I}{\partial x} \approx {\left( {{{GradX}\; 0\left( {i,j} \right)} + {{GradX}\; 1\left( {i,j} \right)}} \right)/2}} & \left\lbrack {{Equation}\mspace{14mu} 11} \right\rbrack \\{\frac{\partial I}{\partial y} \approx {\left( {{{GradY}\; 0\left( {i,j} \right)} + {{GradY}\; 1\left( {i,j} \right)}} \right)/2}} & \left\lbrack {{Equation}\mspace{14mu} 12} \right\rbrack\end{matrix}$

Equation 9 may be arranged as Equation 13 below by using Equations 10through 12.P0(i,j)−P1(i,j)+Vx(i,j)·(GradX0(i,j)+GradX1(i,j)+Vy(i,j)·(GradY0(i,j)+GradY1(i,j))=0  [Equation13]

In Equation 13, since the displacement vector Vx and the displacementvector Vy may change according to a location of the current pixelP(i,j), i.e., are dependent upon (i,j), the displacement vectors Vx andVy may also be respectively represented by Vx(i,j) and Vy(i,j).

Meanwhile, if it is assumed that there is a small uniform movement in avideo sequence in FIG. 22, it is assumed that a pixel of the firstcorresponding region 2210 of the first reference picture most similar tothe current pixel P(i,j) that is pixel unit bi-directional motioncompensated is not the first corresponding pixel P0(i,j) but a firstdisplacement corresponding pixel PA obtained by moving the firstcorresponding pixel P0(i,j) by a predetermined displacement vector Vd.Since it is assumed that there is the small uniform movement in thevideo sequence, it may be assumed that a pixel most similar to thecurrent pixel P(i,j) in the second corresponding region 2220 of thesecond reference picture is a second displacement corresponding pixel PBobtained by moving the second corresponding pixel P1(i,j) by −Vd. Thepredetermined displacement vector Vd consists of the displacement vectorVx in the x-axis direction and the displacement vector Vy in the y-axisdirection, and thus Vd=(Vx, Vy). Accordingly, the pixel unit motioncompensator 2020 according to an embodiment of the present inventioncalculates the displacement vectors Vx and Vy forming the predetermineddisplacement vector Vd, and performs pixel unit motion compensationagain on a value obtained via block unit bi-directional motioncompensation.

The first displacement corresponding pixel PA and the seconddisplacement corresponding pixel PB may be respectively definedaccording to Equations 14 and 15, by using the displacement vector Vx inthe x-axis direction, the displacement vector Vy in the y-axisdirection, the horizontal direction gradient GradX0(i,j) of the firstcorresponding pixel, the vertical direction gradient GradY0(i,j) of thefirst corresponding pixel, the horizontal direction gradient GradX1(i,j)of the second corresponding pixel, and the vertical direction gradientGradY1(i,j) of the second corresponding pixel.PA=P0(i,j)+Vx(i,j)·GradX0(i,j)+Vy(i,j)·GradY0(i,j)  [Equation 14]PB=P1(i,j)·Vx(i,j)·GradX1(i,j)·Vy(i,j)·GradY1(i,j)  [Equation 15]

When Δij indicates a difference between the first displacementcorresponding pixel PA and the second displacement corresponding pixelPB, may be calculated by using Equation 16 below.Δij=PA−PB=P0(i,j)−P1(i,j)+Vx(i,j)·(GradX0(i,j)+GradX1(i,j))+Vy(i,j)·(GradY0(i,j)+GradY1(i,j))  [Equation16]

Comparing Equations 13 and 16, Equation 13 shows a case when Δij is 0,i.e., when values of the first displacement corresponding pixel PA andthe second displacement corresponding pixel PB are the same.

The pixel unit motion compensator 2020 performs pixel unit motioncompensation by using an average value or weighted sum of the values ofthe first and second displacement corresponding pixels PA and PB ofEquations 14 and 15, and at this time, in order to calculate Equations14 and 15, the displacement vectors Vx and Vy, the horizontal directiongradients GradX0(i,j), the vertical direction gradient GradY0(i,j), thehorizontal direction gradient GradX1(i,j), and the vertical directiongradient GradY1(i,j) need to be determined. As described below, agradient of each corresponding pixel may be determined by calculatingthe amount of change in pixel values at a sub-pixel location inhorizontal and vertical directions of the first and second correspondingpixels, or may be calculated by using a predetermined filter.

First, processes of determining the displacement vector Vx in the x-axisdirection and the displacement vector Vx in the y-axis direction will bedescribed.

The pixel unit motion compensator 2020 determines the displacementvectors Vx and Vy that minimize Δij in a window Ωij 2202 having apredetermined size and including adjacent pixels around the currentpixel P(i,j) that is bi-directional motion compensated. It is preferablethat Δij is 0, but since the displacement vectors Vx and Vy that satisfyΔij=0 may not exist with respect to all pixels in the window Ωij 2202,the displacement vectors Vx and Vy that minimize Δij are determined.

FIG. 23 is a reference diagram for describing a process of determining ahorizontal-direction displacement vector and a vertical-directiondisplacement vector, according to an embodiment.

Referring to FIG. 23, a window Ωij 2300 has a size of (2M+1)*(2N+1)(where M and N are each an integer) based on a pixel P(i,j) of a currentblock that is bi-directionally predicted.

When P(i′,j′) indicates a pixel of a current block to bebi-directionally predicted in a window (i′,j′)∈Ωij when i−M≤i′≤i+M andj−M≤j′≤j+M), P0(i′,j′) indicates a pixel value of a first correspondingpixel of a first reference picture 2310 corresponding to the pixelP(i′,j′) of the current block to be bi-directionally predicted,P1(i′,j′) indicates a pixel value of a second corresponding pixel of asecond reference picture 2320 corresponding to the pixel P(i′,j′) of thecurrent block to be bi-directionally predicted, GradX0(i′,j′) indicatesa horizontal-direction gradient of the first corresponding pixel,GradY0(i′,j′) indicates a vertical-direction gradient of the firstcorresponding pixel, GradX1(i′,j′) indicates a horizontal-directiongradient of the second corresponding pixel, and GradY1(i′,j′) indicatesa vertical-direction gradient of the second corresponding pixel, a firstdisplacement corresponding pixel PA′ has a value according to Equation,P0(i′,j′)+Vx*GradX0(i′,j′)+Vy*GradY0(i′,j′), and a second displacementcorresponding pixel PB′ has a value according to Equation,P1(i′,j′)−Vx*GradX1(i′,j′)−Vy*GradY1(i′,j′).

A displacement vector Vx in an x-axis direction and a displacementvector Vy in a y-axis direction, which minimize a difference Δi′j′between the first displacement corresponding pixel PA′ and the seconddisplacement corresponding pixel PB′, may be determined by using amaximum or minimum value of ϕ(Vx,Vy) constituting a sum of squares ofthe difference Δi′j′ according to Equation 17 below.

$\begin{matrix}\begin{matrix}{{\Phi\left( {{Vx},{Vy}} \right)} = {\sum\limits_{i^{\prime},{j^{\prime} \in {\Omega\;{ij}}}}\;\Delta_{i^{\prime}j^{\prime}}^{2}}} \\{= {\sum\limits_{i^{\prime},{j^{\prime} \in {\Omega\;{ij}}}}\;\left( {{P\; 0\left( {i^{\prime},j^{\prime}} \right)} - {P\; 1\left( {i^{\prime},j^{\prime}} \right)} + {{{Vx}\left( {i,j} \right)} \cdot}} \right.}} \\{\left( {{{GradX}\; 0\left( {i^{\prime},j^{\prime}} \right)} + {{GradX}\; 1\left( {i^{\prime},j^{\prime}} \right)}} \right) +} \\\left. {{{Vy}\left( {i,j} \right)} \cdot \left( {{{GradY}\; 0\left( {i^{\prime},j^{\prime}} \right)} + {{GradY}\; 1\left( {i^{\prime},j^{\prime}} \right)}} \right)} \right)^{2}\end{matrix} & \left\lbrack {{Equation}\mspace{14mu} 17} \right\rbrack\end{matrix}$

ϕ(Vx,Vy) is a function using Vx and Vy as parameters, and the maximum orminimum value may be determined by calculating Vx and Vy that make thevalue of partial differentiated ϕ(Vx,Vy) with respect to Vx and Vy to be0 according to Equations 18 and 19 below.

$\begin{matrix}{\frac{\partial{\Phi\left( {{Vx},{Vy}} \right)}}{\partial{Vx}} = {{\sum\limits_{i^{\prime},{j^{\prime} \in {\Omega\;{ij}}}}\;\left\lbrack {{2\;{{{Vx}\left( {i,j} \right)} \cdot \left( {{{GradX}\; 0\left( {i^{\prime},j^{\prime}} \right)} - {{GradX}\; 1\left( {i^{\prime},j^{\prime}} \right)}} \right)^{2}}} - {2{\left( {{{GradX}\; 0\left( {i^{\prime},j^{\prime}} \right)} - {{GradX}\; 1\left( {i^{\prime},j^{\prime}} \right)}} \right) \cdot \left( {{P\; 0\left( {i^{\prime},j^{\prime}} \right)} - {P\; 1\left( {i^{\prime},j^{\prime}} \right)}} \right)}} - {2{\left( {{{GradX}\; 0\left( {i^{\prime},j^{\prime}} \right)} - {{GradX}\; 1\left( {i^{\prime},j^{\prime}} \right)}} \right) \cdot {{Vy}\left( {i,j} \right)} \cdot \left( {{{GradY}\; 0\left( {i^{\prime},j^{\prime}} \right)} - {{GradY}\; 1\left( {i^{\prime},j^{\prime}} \right)}} \right)}}} \right\rbrack} = 0}} & \left\lbrack {{Equation}\mspace{14mu} 18} \right\rbrack \\{\frac{\partial{\Phi\left( {{Vx},{Vy}} \right)}}{\partial{Vy}} = {{\sum\limits_{i^{\prime},{j^{\prime} \in {\Omega\;{ij}}}}\;\left\lbrack {{2\;{{{Vy}\left( {i,j} \right)} \cdot \left( {{{GradY}\; 0\left( {i^{\prime},j^{\prime}} \right)} + {{GradY}\; 1\left( {i^{\prime},j^{\prime}} \right)}} \right)^{2}}} + {2{\left( {{{GradY}\; 0\left( {i^{\prime},j^{\prime}} \right)} + {{GradY}\; 1\left( {i^{\prime},j^{\prime}} \right)}} \right) \cdot \left( {{P\; 0\left( {i^{\prime},j^{\prime}} \right)} - {P\; 1\left( {i^{\prime},j^{\prime}} \right)}} \right)}} + {2{\left( {{{GradY}\; 0\left( {i^{\prime},j^{\prime}} \right)} + {{GradY}\; 1\left( {i^{\prime},j^{\prime}} \right)}} \right) \cdot {{Vx}\left( {i,j} \right)} \cdot \left( {{{GradX}\; 0\left( {i^{\prime},j^{\prime}} \right)} + {{GradX}\; 1\left( {i^{\prime},j^{\prime}} \right)}} \right)}}} \right\rbrack} = 0}} & \left\lbrack {{Equation}\mspace{14mu} 19} \right\rbrack\end{matrix}$

Two linear equations using Vx(i,j) and Vy(i,j) as variables may beobtained as in Equation 20 below from Equations 18 and 19.Vx(i,j)·s1+Vy(i,j)·s2=s3;Vx(i,j)·s4+Vy(i,j)·s5=s6  [Equation 20]

s1 through s6 in Equation 20 are calculated by using Equation 21 below.

$\begin{matrix}{\mspace{79mu}{{{s\; 1} = {\sum\limits_{i^{\prime},{j^{\prime} \in {\Omega\;{ij}}}}\;\left( {{{GradX}\; 0\left( {i^{\prime},j^{\prime}} \right)} + {{GradX}\; 1\left( {i^{\prime},j^{\prime}} \right)}} \right)^{2}}}{{s\; 2} = {{s\; 4} = {\sum\limits_{i^{\prime},{j^{\prime} \in {\Omega\;{ij}}}}\;{\left( {{{GradX}\; 0\left( {i^{\prime},j^{\prime}} \right)} + {{GradX}\; 1\left( {i^{\prime},j^{\prime}} \right)}} \right)\left( {{{{GradY}\; 0\left( {i^{\prime},j^{\prime}} \right)} + {{{GradY}^{\prime}\left( {i^{\prime},j^{\prime}} \right)}s\; 3}} = {- {\sum\limits_{i^{\prime},{j^{\prime} \in {\Omega\;{ij}}}}\;\left( {{{P\; 0\left( {i^{\prime},j^{\prime}} \right)} - {{P^{\prime}\left( {i^{\prime},j^{\prime}} \right)}\left( {{{GradX}\; 0\left( {i^{\prime},j^{\prime}} \right)} + {{GradX}\; 1\left( {i^{\prime},j^{\prime}} \right)}} \right)\mspace{79mu} s\; 5}} = {{\sum\limits_{i^{\prime},{j^{\prime} \in {\Omega\;{ij}}}}\;{\left( {{{GradY}\; 0\left( {i^{\prime},j^{\prime}} \right)} + {{GradY}\; 1\left( {i^{\prime},j^{\prime}} \right)}} \right)^{2}s\; 6}} = {\sum\limits_{i^{\prime},{j^{\prime} \in {\Omega\;{ij}}}}\;{\left( {{P\; 0\left( {i^{\prime},j^{\prime}} \right)} - {P^{\prime}\left( {i^{\prime},j^{\prime}} \right)}} \right)\left( {{{GradY}\; 0\left( {i^{\prime},j^{\prime}} \right)} + {d \cdot {{GradY}^{\prime}\left( {i^{\prime},j^{\prime}} \right)}}} \right)}}}} \right.}}} \right.}}}}}} & \left\lbrack {{Equation}\mspace{14mu} 21} \right\rbrack\end{matrix}$

When simultaneous equations of Equation 21 are solved, values of Vx(i,j)and Vy(i,j) may be obtained according to Vx(i,j)=det1/det andVy(i,j)=det2/det based on Kramer's formulas. In this regard,det1=s3*s5−s2*s6, det2=s1*s6−s3*s4, and det=s1*s5−s2*s4.

Referring back to FIG. 20, the prediction value generator 2030 generatesa bi-directional motion prediction value by adding a block unitbi-directional motion compensation value and a pixel unit motioncompensation value. In more detail, when P_OpticalFlow(i,j) indicates abi-directional motion prediction value of a pixel located at (i,j) of acurrent block, P0(i,j) indicates a pixel value of a first correspondingpixel of a first reference picture corresponding to the pixel located at(i,j) of the current block, GradX0(i,j) indicates a horizontal directiongradient of the first corresponding pixel of the first referencepicture, GradY0(i,j) indicates a vertical direction gradient of thefirst corresponding pixel of the first reference picture, P1(i,j)indicates a pixel value of a second corresponding pixel of a secondreference picture corresponding to the pixel located at (i,j) of thecurrent block, GradX1(i,j) indicates a horizontal direction gradient ofthe second corresponding pixel of the second reference picture,GradY1(i,j) indicates a vertical direction gradient of the secondcorresponding pixel of the second reference picture, Vx indicates ahorizontal direction displacement vector, and Vy indicates a verticaldirection displacement vector, the prediction value generator 2030generates the bi-directional motion prediction value by using Equation22 below.

$\begin{matrix}{P_{{OpticalFlow}{({i,j})}} = {\frac{{P\; 0\left( {i,j} \right)} + {P\; 1\left( {i,j} \right)}}{2} + {\left( {{{Vx} \cdot \left( {{{GradX}\; 0\left( {i,j} \right)} - {{GradX}\; 1\left( {i,j} \right)}} \right)} + {{Vy} \cdot \left( {{{GradY}\; 0\left( {i,j} \right)} - {{GradY}\; 1\left( {i,j} \right)}} \right)}} \right)/2}}} & \left\lbrack {{Equation}\mspace{14mu} 22} \right\rbrack\end{matrix}$

In Equation 22, (P0(i,j)+P1(i,j))/2 corresponds to a block unitbi-directional motion compensation value and(Vx*(GradX0(i,j)−GradX1(i,j))+Vy*(GradY0(i,j)−GradY1(i,j)))/2corresponds to a pixel unit motion compensation value calculatedaccording to an embodiment.

Equation 22 may be modified to Equation 23 below by multiplying apredetermined weight α to the pixel unit motion compensation value.

$\begin{matrix}{P_{{OpticalFlow}{({i,j})}} = {\frac{{P\; 0\left( {i,j} \right)} + {P\; 1\left( {i,j} \right)}}{2} + {\left( {{{aVx} \cdot \left( {{{GradX}\; 0\left( {i,j} \right)} - {{GradX}\; 1\left( {i,j} \right)}} \right)} + {{aVy} \cdot \left( {{{GradY}\; 0\left( {i,j} \right)} - {{GradY}\; 1\left( {i,j} \right)}} \right)}} \right)/2}}} & \left\lbrack {{Equation}\mspace{14mu} 23} \right\rbrack\end{matrix}$

Here, the weight α may be smaller than 1, preferably, α=0.56±0.05.

Equation 16 above is calculated assuming that a temporal distance d0between the current picture and the first reference picture and atemporal distance d1 between the current picture and the secondreference picture are both 1. If d0 and d1 are not 1, a size of thepredetermined displacement vector Vd may be scaled in inverse proportionto d0 and d1. That is, when (Vx0, Vy0) indicates a displacement vectorof a first reference picture indicating a first displacementcorresponding pixel in a first corresponding pixel and (Vx1, Vy1)indicates a displacement vector of a second reference picture indicatinga second displacement corresponding pixel in a second correspondingpixel, d0*Vx1=−d1*Vx0 and d0*Vy1=−d1*Vy0. The displacement vectors Vxand Vy may be calculated by calculating maximum and minimum values bypartial differentiating a function ϕ(Vx,Vy) with respect to thedisplacement vectors Vx and Vy when d=d1/d0. As described above,Vx(i,j)=det1/det, Vy(i,j)=det2/det, det1=s3*s5−s2*s6, det2=s1*s6−s3*s4,and det=s1*s5−s2*s4. Here, values of s1 through s6 are calculatedaccording to Equation 24 below.

$\begin{matrix}{\mspace{79mu}{{{s\; 1} = {\sum\limits_{i^{\prime},{j^{\prime} \in {\Omega\;{ij}}}}\;\left( {{{GradX}\; 0\left( {i^{\prime},j^{\prime}} \right)} + {{d \cdot {GradX}}\; 1\left( {i^{\prime},j^{\prime}} \right)}} \right)^{2}}}{{s\; 2} = {{s\; 4} = {\sum\limits_{i^{\prime},{j^{\prime} \in {\Omega\;{ij}}}}\;{\left( {{{GradX}\; 0\left( {i^{\prime},j^{\prime}} \right)} + {{d \cdot {GradX}}\; 1\left( {i^{\prime},j^{\prime}} \right)}} \right)\left( {{{{GradY}\; 0\left( {i^{\prime},j^{\prime}} \right)} + {{d \cdot {{GradY}^{\prime}\left( {i^{\prime},j^{\prime}} \right)}}s\; 3}} = {- {\sum\limits_{i^{\prime},{j^{\prime} \in {\Omega\;{ij}}}}\;\left( {{{P\; 0\left( {i^{\prime},j^{\prime}} \right)} - {{P^{\prime}\left( {i^{\prime},j^{\prime}} \right)}\left( {{{GradX}\; 0\left( {i^{\prime},j^{\prime}} \right)} + {{d \cdot {GradX}}\; 1\left( {i^{\prime},j^{\prime}} \right)}} \right)\mspace{79mu} s\; 5}} = {{\sum\limits_{i^{\prime},{j^{\prime} \in {\Omega\;{ij}}}}\;{\left( {{{GradY}\; 0\left( {i^{\prime},j^{\prime}} \right)} + {{d \cdot {GradY}}\; 1\left( {i^{\prime},j^{\prime}} \right)}} \right)^{2}s\; 6}} = {\sum\limits_{i^{\prime},{j^{\prime} \in {\Omega\;{ij}}}}\;{\left( {{P\; 0\left( {i^{\prime},j^{\prime}} \right)} - {P^{\prime}\left( {i^{\prime},j^{\prime}} \right)}} \right)\left( {{{GradY}\; 0\left( {i^{\prime},j^{\prime}} \right)} + {d \cdot {{GradY}^{\prime}\left( {i^{\prime},j^{\prime}} \right)}}} \right)}}}} \right.}}} \right.}}}}}} & \left\lbrack {{Equation}\mspace{14mu} 24} \right\rbrack\end{matrix}$

Also, when the temporal distance d0 and the temporal distance d1 are not1, Equation 23 is modified to Equation 25, and the prediction valuegenerator 2030 generates the bi-directional motion compensation value byusing Equation 25.

$\begin{matrix}{P_{{OpticalFlow}{({i,j})}} = {\frac{{P\; 0\left( {i,j} \right)} + {P\; 1\left( {i,j} \right)}}{2} + {\left( {{{aVx} \cdot \left( {{{GradX}\; 0\left( {i,j} \right)} - {{d \cdot {GradX}}\; 1\left( {i,j} \right)}} \right)} + {{aVy} \cdot \left( {{{GradY}\; 0\left( {i,j} \right)} - {{d \cdot {GradY}}\; 1\left( {i,j} \right)}} \right)}} \right)/2}}} & \left\lbrack {{Equation}\mspace{14mu} 25} \right\rbrack\end{matrix}$

Meanwhile, the optical flow of Equation 9 described above is based onthe assumption that the amount of change in pixel values according totime is 0, but a pixel value may change according to time. When qindicates the amount of change in pixel values according to time,Equation 9 is modified to Equation 26 below.

$\begin{matrix}{{\frac{\partial I}{\partial t} + {{Vx} \cdot \frac{\partial I}{\partial x}} + {{Vy} \cdot \frac{\partial I}{\partial y}}} = q} & \left\lbrack {{Equation}\mspace{14mu} 26} \right\rbrack\end{matrix}$

In this regard, q indicates an average of differences of pixel values infirst and second corresponding regions, and may be calculated by usingEquation 27 below.

$\begin{matrix}{q = \frac{{\sum\limits_{i,{j \in {block}}}{P\; 1\left( {i,j} \right)}} - {P\; 0\left( {i,j} \right)}}{{2 \cdot {Hor\_ block}}{{\_ Size} \cdot {ver\_ block}}{\_ Size}}} & \left\lbrack {{Equation}\mspace{14mu} 27} \right\rbrack\end{matrix}$

Hor_block_size indicates a horizontal direction size of a current blockand ver_block_size indicates a vertical direction size of the currentblock. When the displacement vectors Vx and Vy are calculated by using avalue of P1(i,j)−q considering the amount of change q, instead ofP1(i,j) in Equations 14 through 25, Vx(i,j)=det1/det, Vy(i,j)=det2/det,det1=s3*s5−s2*s6, det2=s1*s6−s3*s4, and det=s1*s5−s2*s4. Here, values ofs1 through s6 are calculated according to Equation 28 below.

$\begin{matrix}{\mspace{79mu}{{{s\; 1} = {\sum\limits_{i^{\prime},{j^{\prime} \in {\Omega\;{ij}}}}\;\left( {{{GradX}\; 0\left( {i^{\prime},j^{\prime}} \right)} + {{d \cdot {GradX}}\; 1\left( {i^{\prime},j^{\prime}} \right)}} \right)^{2}}}{{s\; 2} = {{s\; 4} = {\sum\limits_{i^{\prime},{j^{\prime} \in {\Omega\;{ij}}}}\;{\left( {{{GradX}\; 0\left( {i^{\prime},j^{\prime}} \right)} + {{d \cdot {GradX}}\; 1\left( {i^{\prime},j^{\prime}} \right)}} \right)\left( {{{{GradY}\; 0\left( {i^{\prime},j^{\prime}} \right)} + {{d \cdot {{GradY}^{\prime}\left( {i^{\prime},j^{\prime}} \right)}}s\; 3}} = {{- {\sum\limits_{i^{\prime},{j^{\prime} \in {\Omega\;{ij}}}}\;{\left( {{P\; 0\left( {i^{\prime},j^{\prime}} \right)} - {P^{\prime}\left( {i^{\prime},j^{\prime}} \right)} - q} \right)\left( {{{GradX}\; 0\left( {i^{\prime},j^{\prime}} \right)} + {{d \cdot {GradX}}\; 1\left( {i^{\prime},j^{\prime}} \right)}} \right)\mspace{79mu} s\; 5}}} = {{\sum\limits_{i^{\prime},{j^{\prime} \in {\Omega\;{ij}}}}\;{\left( {{{GradY}\; 0\left( {i^{\prime},j^{\prime}} \right)} + {{d \cdot {GradY}}\; 1\left( {i^{\prime},j^{\prime}} \right)}} \right)^{2}s\; 6}} = {\sum\limits_{i^{\prime},{j^{\prime} \in {\Omega\;{ij}}}}\;{\left( {{P\; 0\left( {i^{\prime},j^{\prime}} \right)} - {P^{\prime}\left( {i^{\prime},j^{\prime}} \right)} - q} \right)\left( {{{GradY}\; 0\left( {i^{\prime},j^{\prime}} \right)} + {d \cdot {{GradY}^{\prime}\left( {i^{\prime},j^{\prime}} \right)}}} \right)}}}}} \right.}}}}}} & \left\lbrack {{Equation}\mspace{14mu} 28} \right\rbrack\end{matrix}$

Here, the prediction value generator 2030 may also generate thebi-directional motion compensation value according to Equation 25 above.

As described above, horizontal and vertical direction gradients may beobtained by calculating the amount of change at a sub-pixel location inhorizontal and vertical directions of first and second correspondingpixels, or by using a predetermined filter.

FIG. 24 is a reference diagram for describing a process of calculatinghorizontal and vertical direction gradients, according to an embodiment.Referring to FIG. 24, a horizontal direction gradient GradX0(i,j) and avertical direction gradient GradY0(i,j) of a first corresponding pixelP0(i,j) 2410 of a first reference picture may be calculated byrespectively obtaining the amount of change in pixel values at adjacentsub-pixel locations in a horizontal direction of the first correspondingpixel P0(i,j) 2410 and the amount of change in pixel values at adjacentsub-pixel locations in a vertical direction. That is, the horizontaldirection gradient GradX0(i,j) may be calculated by calculating theamount of change in pixel values of a sub-pixel P0(i−h,j) 2460 and a subpixel P0(i+h,j) 2470 distant from the first corresponding pixel P0(i,j)2410 by h (where h is a fraction smaller than 1) in a horizontaldirection, and the vertical direction gradient GradY0(i,j) may becalculated by calculating the amount of change in pixel values of asub-pixel P0(i,j−h) 2480 and a sub pixel P0(i,j+h) 2490 distant from thefirst corresponding pixel P0(i,j) 1710 by h in a vertical direction, byusing Equation 29 below.

$\begin{matrix}{{{{{GradX}\; 0\left( {i,j} \right)} = \frac{{P\; 0\left( {{i + h},j} \right)} - {P\; 0\left( {{i - h},j} \right)}}{2\; h}};}{{{GradY}\; 0\left( {i,j} \right)} = \frac{{P\; 0\left( {i,{j + h}} \right)} - {P\; 0\left( {i,{j - h}} \right)}}{2\; h}}} & \left\lbrack {{Equation}\mspace{14mu} 29} \right\rbrack\end{matrix}$

Values of the sub-pixels P0(i−h,j) 2460, P0(i+h,j) 2470, P0(i,j−h) 2480,and P0(i, j+h) 2490 may be calculated by using a general interpolationmethod. Also, gradients of a second corresponding pixel of a secondreference picture may be calculated in a similar manner as Equation 29.

According to an embodiment, a gradient of each corresponding pixel maybe calculated by using a predetermined filter, instead of calculatingthe amount of change in pixel values at sub-pixel locations according toEquation 29.

FIG. 25 is a reference diagram for describing a process of calculatinghorizontal and vertical direction gradients, according to anotherembodiment, and FIG. 26 is a table showing filter coefficients of agradient calculating filter, according to another embodiment.

According to the other embodiment, a gradient may be determined byapplying a predetermined filter to pixels of a reference picture.Referring to FIG. 25, a horizontal direction gradient of a correspondingpixel P0 2500 may be calculated by applying a predetermined pixel on Mpixels 2520 to the left of the corresponding pixel P0 2500 and M pixels2510 to the right of the corresponding pixel P0 2500. A filtercoefficient used at this time may be determined according to a value ofM used to determine a size of a window and a value of α indicating aninterpolation location between integer pixels, as shown in FIG. 26. Forexample, when 2M=4 and a sub-pixel is distant from the correspondingpixel P0 2500 by ¼, i.e., α=¼, filter coefficients {−8. −36. 54, −10} ona second row of FIG. 26 are applied to adjacent pixels P-2, P-1, P1, andP2. Here, a horizontal direction gradient GradX0 of the correspondingpixel P0 2500 may be calculated based on a weighted sum of a filtercoefficient and an adjacent pixel, according to equation, GradX0=−8*P-2,−36*P-1+54*P1−10*P2+128>>8. Similarly, a vertical direction gradient isalso calculated by applying filter coefficients of FIG. 26 to adjacentpixels according to a size 2N of a window and an interpolation location.Here, 2M of FIG. 26 may be replaced by 2N.

An operation of pixel unit motion compensation according to anembodiment may be limited by a predetermined condition. The pixel unitmotion compensation according to an embodiment may be performed based ona block size. For example, when the block size is smaller than apredetermined size, the pixel unit motion compensation may not beperformed.

The image decoding apparatus 200 according to an embodiment may limitthe performing of the pixel unit motion compensation due to anothersyntax element. For example, when a coded block flag (CBF) is not 0, thepixel unit motion compensation may not be performed. Also, when theimage decoding apparatus 200 performs prediction by using an AMVP modein which a motion vector prediction value is derived from an adjacentblock, or a merge mode in which a reference direction, a referencepicture index, and a motion vector prediction value are derived from theadjacent block, the performing of the pixel unit motion compensation maybe limited. Also, for example, even when local illumination compensationis performed or affine motion compensation is performed, the pixel unitmotion compensation may not be performed.

Thus, the image decoding apparatus 200 may determine whether to performthe pixel unit motion compensation, based on a coded block flag (CBF), asyntax element indicating whether to perform motion compensation (e.g.,an AMVP mode and a merge mode) by using derived motion information, asyntax element indicating whether to perform local illuminationcompensation, a syntax element indicating whether to perform affinemotion compensation, or the like. In this regard, the CBF, theinformation indicating whether to perform motion compensation by usingderived motion information, the information indicating whether toperform local illumination compensation, and the information indicatingwhether to perform affine motion compensation may be informationindicating information denoting whether the pixel unit motioncompensation is limited.

FIG. 27 is a flowchart of an image encoding method, according to anembodiment.

Referring to FIG. 27, in operation S2710, the image encoding apparatus100 performs bi-directional motion prediction for determining a firstmotion vector and a second motion vector respectively indicating a firstcorresponding region and a second corresponding region which are mostsimilar to a current block in a first reference picture and a secondreference picture.

In operation S2720, the image encoding apparatus 100 performs block unitbi-directional motion compensation on the current block by using thefirst motion vector and the second motion vector.

In operation S2730, the image encoding apparatus 100 performs pixel unitmotion compensation on each pixel of the current block by using pixelsof the first reference picture and the second reference picture. Asdescribed above, the image encoding apparatus 100 may generate a pixelunit motion compensation value of each pixel of the current block byusing horizontal and vertical direction gradients of a firstcorresponding pixel of the first reference picture corresponding to eachpixel of the current block, horizontal and vertical direction gradientsof a second corresponding pixel of the second reference picturecorresponding to each pixel of the current block, and horizontal andvertical direction displacement vectors determined by using the pixelsof the first reference picture and the second reference picture.

In operation S2740, the image encoding apparatus 100 generates abi-directional motion prediction value of the current block by adding aresult of the block unit bi-directional motion compensation and a resultof the pixel unit motion compensation. A residual signal that is adifference between the predicted bi-directional motion prediction valueand an original input signal is then encoded in the form of a bitstreamvia transformation, quantization, and entropy encoding. Meanwhile,according to an embodiment, when the pixel unit motion compensationvalue is used, predetermined index information indicating usage ornon-usage of the pixel unit motion compensation value may be added tothe encoded bitstream because the pixel unit motion compensation valueis different from a general bi-directional motion prediction value.

FIG. 28 is a flowchart of an image decoding method, according to anembodiment.

Referring to FIG. 28, in operation S2810, the image decoding apparatus200 receives a bitstream.

In operation S2820, the image decoding apparatus 200 determines whetherto perform pixel unit motion compensation on a current block, based oninformation about whether pixel unit motion compensation is limited, theinformation being extracted from the bitstream.

In operation S2830, when the pixel unit motion compensation isperformed, information about a first motion vector and a second motionvector respectively indicating a first corresponding region and a secondcorresponding region which are most similar to the current block in afirst reference picture and a second reference picture is extracted fromthe bitstream.

In operation S2840, the image decoding apparatus 200 performs block unitbi-directional motion compensation on the current block by using thefirst motion vector and the second motion vector.

In operation S2850, the image decoding apparatus 200 performs pixel unitmotion compensation on each pixel of the current block by using pixelsof the first reference picture and a second reference picture. Asdescribed above, the image decoding apparatus 200 may generate a pixelunit motion compensation value of each pixel of the current block byusing horizontal and vertical direction gradients of a firstcorresponding pixel of the first reference picture corresponding to eachpixel of the current block, horizontal and vertical direction gradientsof a second corresponding pixel of the second reference picturecorresponding to each pixel of the current block, and horizontal andvertical direction displacement vectors determined by using pixels ofthe first reference picture and the second reference picture.

In operation S2860, the image decoding apparatus 200 generates abi-directional motion prediction value of the current block by using aresult of the block unit bi-directional motion compensation and a resultof the pixel unit motion compensation. The bi-directional motionprediction value of the current block is added to a residual value ofthe current block, which is extracted from the bitstream and decoded, toreconstruct the current block.

While this disclosure has been particularly shown and described withreference to embodiments thereof, it will be understood by those ofordinary skill in the art that various changes in form and details maybe made therein without departing from the spirit and scope of thedisclosure as defined by the appended claims. The embodiments should beconsidered in a descriptive sense only and not for purposes oflimitation. Therefore, the scope of the disclosure is defined not by thedetailed description of the disclosure but by the appended claims, andall differences within the scope will be construed as being included inthe present disclosure.

The embodiments of the present disclosure can be written as computerprograms and can be implemented in general-use digital computers thatexecute the programs using a computer readable recording medium.Examples of the computer readable recording medium include magneticstorage media (e.g., ROM, floppy disks, hard disks, etc.), opticalrecording media (e.g., CD-ROMs, or DVDs), etc.

The invention claimed is:
 1. An entropy decoding method comprising:obtaining, probability information used in performing arithmeticdecoding on a current bin by updating, by using a first probabilitymodel and a second probability model, previous probability informationthat was used in performing arithmetic decoding on a previous bin;obtaining the current bin by performing arithmetic decoding based on theobtained probability information; and obtaining a syntax element byde-binarizing the obtained current bin, wherein the first probabilitymodel and the second probability model each use a size of a window, anda size of a window of the first probability model is less than a size ofa window of the second probability model, and wherein at least one ofthe size of the window of the first probability model and the size ofthe window of the second probability model are determined based on atype of a current slice or a type of a current picture.
 2. The entropydecoding method of claim 1, wherein one of the size of the window of thefirst probability model and the size of the window of the secondprobability model are obtained from the bitstream.
 3. The entropydecoding method of claim 1, wherein one of the size of the window of thefirst probability model and the size of the window of the secondprobability model has a fixed value.
 4. The entropy decoding method ofclaim 1, wherein the type of the current slice or the type of thecurrent picture is one of I slice (or picture), P slice (or picture),and B slice (or picture).